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公开(公告)号：US20240370668A1
公开(公告)日：2024-11-07
申请号：US18031511
申请日：2022-03-08
Inventor： Boran JIANG , Chao JI , Hongxiang SHEN , Zhenzhong ZHANG , Ge OU , Chuqian ZHONG , Shuqi WEI , Pengfei ZHANG
IPC: G06F40/58
Abstract: The present disclosure relates to a method for training a natural language processing model, including: obtaining a sample text of natural language; determining one or more triples in the sample text, wherein each of the triples comprises two entities in the sample text and a relation between the two entities; processing the sample text based on the triples to obtain one or more knowledge fusion vectors; and training a natural language processing model by inputting the knowledge fusion vectors into the natural language processing model to obtain a target model.
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公开(公告)号：US20250037443A1
公开(公告)日：2025-01-30
申请号：US18279857
申请日：2022-11-24
Inventor： Chao JI , Boran JIANG , Ge OU , Shuqi WEI , Pengfei ZHANG , Chuqian ZHONG
IPC: G06V10/80 , G06T5/60 , G06V10/77 , G06V10/774 , G06V10/82
Abstract: A model training method includes: acquiring a sample set including a plurality of sample groups; the sample group includes an original image sample and original text samples; performing mask processing on the original image sample and the original text samples to generate a mask image sample and mask text samples; using the mask image sample and the mask text samples to perform adversarial training on a generator and a discriminator to obtain a target model; the generator includes a feature extraction network and an output network, the feature extraction network is used to perform feature extraction after information fusion of an input image and an input text of the generator.
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Patent Agency Ranking
公开(公告)号：US20250005356A1
公开(公告)日：2025-01-02
申请号：US18707804
申请日：2023-07-31
Inventor： Shuqi WEI , Pengfei ZHANG , Chuqian ZHONG
Abstract: Provided is an object operating method, includes: acquiring an object to be operated; inputting the object to be operated into a target model, wherein the target model is a trained neural network model and at least one set of parameters in the target model is acquired in a predetermined manner, and the target model is configured to carry out a recognition operation or a processing operation on the object to be operated; and acquiring an operation result output by the target model; wherein the predetermined manner includes: acquiring a collection of sample parameters corresponding to a first set of parameters of the target model, performing a plurality of iteration processing on the collection of sample parameters; acquiring a target set of parameters based on the collection of sample parameters subjected to the plurality of iteration processing; and determining the target set of parameters as the first set of parameters.
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公开(公告)号：US20240303507A1
公开(公告)日：2024-09-12
申请号：US18026327
申请日：2022-03-30
Inventor： Boran JIANG , Ge OU , Chao JI , Chuqian ZHONG , Shuqi WEI , Pengfei ZHANG
IPC: G06N5/02 , G06Q30/0601
CPC classification number: G06N5/02 , G06Q30/0631
Abstract: Provided are a method and device for recommending goods, a method and device for training a goods knowledge graph, and a method and device for training a model. The method for training a goods knowledge graph includes: constructing an initial goods knowledge graph based on a first type of triples and a second type of triples, where a format of the first type of triples is head entity-relation-tail entity, and a format of the second type of triples is entity-attribute-attribute value (S101); and training the initial goods knowledge graph based on a graph embedding model to obtain embedding vectors of entities in the trained goods knowledge graph (S102).
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公开(公告)号：US20250054280A1
公开(公告)日：2025-02-13
申请号：US18280299
申请日：2022-09-30
Inventor： Chao JI , Ge OU , Chuqian ZHONG , Pengfei ZHANG , Boran JIANG , Shuqi WEI
IPC: G06V10/774 , G06F40/279 , G06V10/40
Abstract: The present disclosure provides a training method and apparatus for an image-text matching model, a device and a storage medium. The method includes: acquiring a positive sample and a negative sample; where the positive sample includes text and an image, the text in the positive sample is used to describe content of the image in the positive sample; the negative sample includes text and an image, the text in the negative sample describes content that is inconsistent with content of the image in the negative sample; training the image-text matching model by using the acquired positive sample and the acquired negative sample based on a manner of contrastive learning; where the image-text matching model is used to predict, for an input image and input text, whether the input text is used to describe content of the input image.
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公开(公告)号：US20240320428A1
公开(公告)日：2024-09-26
申请号：US18638457
申请日：2024-04-17
Applicant: BOE Technology Group Co., Ltd.
Inventor： Pengfei ZHANG , Chao JI , Boran JIANG , Ge OU , Chuqian ZHONG , Shuqi WEI
IPC: G06F40/279 , G06V30/19
CPC classification number: G06F40/279 , G06V30/1912 , G06V30/19127 , G06V30/1916
Abstract: Provided in the present disclosure are a text recognition method, and a model and an electronic device, which are applied to a mode in which primary classification is first performed from different dimensions, and secondary classification is then performed, such that the meaning of text is analyzed from different dimensions, thereby improving the accuracy of text recognition. The method includes: acquiring text to be recognized, and performing primary classification on the text to obtain a plurality of text features, wherein the primary classification is used for performing feature extraction on the text from different dimensions, and there are differences between features extracted from the different dimensions (100); splicing the plurality of text features, so as to obtain spliced features (101); and performing secondary classification on the spliced features to obtain a text category corresponding to the text, wherein the secondary classification is used for classifying the spliced features (102).
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公开(公告)号：US20240303798A1
公开(公告)日：2024-09-12
申请号：US18263230
申请日：2021-11-30
Inventor： Chao JI , Yaoping WANG , Hongxiang SHEN , Ge OU , Boran JIANG , Shuqi WEI , Chuqian ZHONG , Pengfei ZHANG
IPC: G06T7/00
CPC classification number: G06T7/0004 , G06T2207/20021 , G06T2207/20081 , G06T2207/20084 , G06T2207/30121
Abstract: The present disclosure relates to an image recognition method and system for a display panel, a training method, and an electronic device and a non-volatile computer-readable storage medium. The image recognition method includes: acquiring an image of a display panel, wherein the image includes gate lines extending in a first direction and data lines extending in a second direction, the gate lines and the data lines intersecting to define a plurality of sub-pixel regions, and the image further includes a defect pattern; and recognizing the defect pattern in the image by using an image recognition model to obtain defect information, wherein the defect information includes at least one of a defect type or a defect position of the defect pattern, the image recognition model comprises a first attention model configured to learn a weight proportion of a feature of the defect pattern in the image.
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